Abstract
Traditional random search methods incorporate symmetric density functions for generating perturbations about the operating point. This philosophy has been retained in the development of multi-agent stochastic search techniques including methods in evolutionary computation. The present work introduces asymmetric mutations for stochastic search. The asymmetric mutations are generated via a probabilistic switching mechanism that biases the search based on self-adaptive strategy parameters. The dynamics of the strategy parameters are explored and then investigated in light of using asymmetric perturbations.
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© 1998 Springer-Verlag Berlin Heidelberg
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McDonnell, J.R. (1998). Asymmetric mutations for stochastic search. In: Porto, V.W., Saravanan, N., Waagen, D., Eiben, A.E. (eds) Evolutionary Programming VII. EP 1998. Lecture Notes in Computer Science, vol 1447. Springer, Berlin, Heidelberg. https://doi.org/10.1007/BFb0040822
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DOI: https://doi.org/10.1007/BFb0040822
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